Information processing apparatus, information processing method, program, and information processing system

ABSTRACT

An information processing apparatus according to an embodiment of the present technology includes an acquisition unit, an image generation unit, and a presentation unit. The acquisition unit acquires image data relating to a predetermined region on a map. The image generation unit generates a predicted image on the basis of the image data, the predicted image being predicted to be acquired when imaging is performed within the predetermined region. The presentation unit presents the predicted image on the basis of an instruction relating to generation of plan information relating to movement and imaging of a mobile body having an imaging function within the predetermined region.

TECHNICAL FIELD

The present technology relates to an information processing apparatus,an information processing method, a program, and an informationprocessing system that are applicable to control of autonomous movementof a mobile body.

BACKGROUND ART

Patent Literature 1 discloses a technique for simulating a moving routeof an aircraft or the like that performs aerial photogrammetry. In thesimulation method described in Patent Literature 1, an imaging coursefor which an imaging condition such as a focal length and a thresholdvalue regarding the size of an unphotographable region are set is inputto a computer. When the size of a region within the set imaging courseexceeds the threshold value, that region is determined to be anunphotographable region. Further, when the ratio of the determinedunphotographable region occupying the imaging course is large, theimaging course is determined to be unsuitable for a simulation. As aresult, an imaging course capable of capturing an effective aerialphotograph is established by one imaging flight, which allowsinexpensive and accurate aerial photogrammetry (paragraphs [0013] and[0028], FIGS. 1 and 3, and the like of Patent Literature 1).

CITATION LIST Patent Literature

Patent Literature 1: Japanese Patent Application Laid-open No.2001-141452

DISCLOSURE OF INVENTION Technical Problem

As described above, there is a demand for a technique that makes itpossible to generate plan information, which is obtained by predicting acaptured image or video in advance before moving and by verifying suchan image or video, for the movement and imaging of a mobile body havingan imaging function.

In view of the above circumstances, it is an object of the presenttechnology to provide an information processing apparatus, aninformation processing method, a program, and an information processingsystem that are capable of generating plan information for movement andimaging of a mobile body having an imaging function.

Solution to Problem

In order to achieve the above object, an information processingapparatus according to an embodiment of the present technology includesan acquisition unit, an image generation unit, and a presentation unit.

The acquisition unit acquires image data relating to a predeterminedregion on a map.

The image generation unit generates a predicted image on the basis ofthe image data, the predicted image being predicted to be acquired whenimaging is performed within the predetermined region.

The presentation unit presents the predicted image on the basis of aninstruction relating to generation of plan information relating tomovement and imaging of a mobile body having an imaging function withinthe predetermined region.

In this information processing apparatus, the image data relating to thepredetermined region on the map is acquired. The predicted imagepredicted to be acquired when imaging is performed within thepredetermined region is generated on the basis of the image data. Thepredicted image is presented on the basis of the instruction relating tothe generation of the plan information relating to the movement andimaging of the mobile body having an imaging function in thepredetermined region. As a result, the plan information can be generatedfor the movement and imaging of the mobile body having the imagingfunction.

The presentation unit may output a graphical user interface (GUI)including the predicted image for inputting the instruction relating tothe generation of the plan information.

The image generation unit may generate the predicted image on the basisof an instruction relating to at least one of a position within thepredetermined region or an imaging condition.

The imaging condition may include at least one of an imaging direction,an imaging time, or environment information relating to thepredetermined region.

The image generation unit may generate, on the basis of an instructionto select an object present within the predetermined region, thepredicted image in which the object is imaged.

The image generation unit may generate the predicted image on the basisof a generation rule of the predicted image relating to the instructionto select the object.

The generation rule may include classification information forclassifying the object and at least one of information of a relativeimaging position relative to the object or information of a displaystate of the object within the predicted image, as informationassociated with the classification information.

The image generation unit may generate the predicted image by generatinga prediction candidate image on the basis of position information of theobject serving as a selection target and evaluating the predictioncandidate image regarding a display state of the object within thepredicted image.

The information processing apparatus may further include a plangeneration unit that generates the plan information on the basis of aninput instruction relating to the generation of the plan information.

The plan generation unit may generate the plan information on the basisof an instruction to select the presented predicted image.

The plan information may include at least one of a transit point, amoving time, or an imaging condition.

The image data may be image data acquired when a scanning mobile bodyhaving an imaging function performs imaging while scanning thepredetermined region.

The image data may include omnidirectional image data.

The information processing apparatus may further include a control unitthat controls an operation relating to the movement and the imaging ofthe mobile body having the imaging function on the basis of the planinformation.

The information processing apparatus may further include a scanninggeneration unit that generates scanning plan information relating toscanning and imaging of the scanning mobile body within thepredetermined region.

The scanning plan information may include cost information relating to ascanning route. In this case, the cost information may be generated onthe basis of a scanning route that has been taken in a past.

An information processing method according to an embodiment of thepresent technology is an information processing method executed by acomputer system, and includes: acquiring image data relating to apredetermined region on a map; generating a predicted image on the basisof the image data, the predicted image being predicted to be acquiredwhen imaging is performed within the predetermined region; andpresenting the predicted image on the basis of an instruction relatingto generation of plan information relating to movement and imaging of amobile body having an imaging function within the predetermined region.

A program according to an embodiment of the present technology causes acomputer system to execute the steps of: acquiring image data relatingto a predetermined region on a map; generating a predicted image on thebasis of the image data, the predicted image being predicted to beacquired when imaging is performed within the predetermined region; andpresenting the predicted image on the basis of an instruction relatingto generation of plan information relating to movement and imaging of amobile body having an imaging function within the predetermined region.

An information processing system according to an embodiment of thepresent technology includes an information processing apparatus and amobile body.

The information processing apparatus includes an acquisition unit, animage generation unit, a presentation unit, a plan generation unit.

The acquisition unit acquires image data relating to a predeterminedregion on a map.

The image generation unit generates a predicted image on the basis ofthe image data, the predicted image being predicted to be acquired whenimaging is performed within the predetermined region.

The presentation unit presents the predicted image on the basis of aninstruction relating to generation of plan information relating tomovement and imaging of a mobile body having an imaging function withinthe predetermined region.

The plan generation unit generates the plan information on the basis ofan input instruction relating to the generation of the plan information.

The mobile body includes an imaging unit and performs imaging whilemoving within the predetermined region on the basis of the planinformation generated by the information processing apparatus.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram showing a configuration example of a droneimaging system according to a first embodiment.

FIG. 2 is a flowchart showing the outline of an imaging example usingthe drone imaging system.

FIG. 3 is a block diagram showing a functional configuration example ofa server apparatus.

FIG. 4 is a schematic diagram showing an example of a plan generatingGUI.

FIG. 5 is a flowchart showing a specific example of processing forgenerating the scenario plan information.

FIG. 6 is a block diagram showing functional configuration examples of ascanning drone and the server apparatus.

FIG. 7 is a schematic diagram showing a scanning plan generating GUI forexecuting the scanning of the scanning drone.

FIG. 8 is a schematic diagram showing a specific example of the scanningof the scanning drone.

FIG. 9 is a block diagram showing a functional configuration example ofa server apparatus according to a second embodiment.

FIG. 10 is a schematic diagram showing an example of a plan generatingGUI when a candidate image is used.

FIG. 11 is a flowchart showing a specific example of processing forgenerating scenario plan information using a candidate image.

FIG. 12 is a diagram showing an example of imaging rules.

FIG. 13 is a block diagram showing a functional configuration example ofa server apparatus according to a third embodiment.

FIG. 14 is a flowchart showing a determination example for generating acandidate image.

FIG. 15 is a block diagram showing a hardware configuration example ofthe server apparatus.

MODE(S) FOR CARRYING OUT THE INVENTION

Embodiments according to the present technology will now be describedbelow with reference to the drawings.

First Embodiment

[Drone Imaging System]

FIG. 1 is a schematic diagram showing a configuration example of a droneimaging system 100 according to a first embodiment of the presenttechnology. A drone imaging system 100 corresponds to one embodiment ofan information processing system according to the present technology.

The drone imaging system 100 includes a server apparatus 10, a userterminal 30, and a drone 50. The server apparatus 10, the user terminal30, and the drone 50 are communicably connected to each other via anetwork 35.

The network 35 is constructed by, for example, the Internet or a widearea communication network. In addition, any wide area network (WAN),any local area network (LAN), or the like may be used, and a protocolfor constructing the network 35 is not limited.

The server apparatus 10 is capable of providing an application servicerelating to the drone imaging system 100. In this embodiment, the serverapparatus 10 generates plan information of the drone 50 on the basis ofan instruction of a user 31. The plan information is plan informationrelating to the movement and imaging within a predetermined region on amap, and will be described later in detail. The server apparatus 10serves as an embodiment of an information processing apparatus accordingto the present technology.

The server apparatus 10 includes a database 5 and allows the database 5to store various types of information regarding the drone imaging system100. The server apparatus 10 is also capable of reading various types ofinformation from the database 5 and outputting them to the user terminal30 or the like.

The user terminal 30 includes a variety of devices that can be used bythe user 31. For example, a personal computer (PC), a smartphone, or thelike is used as the user terminal 30. The user 31 can use the droneimaging system 100 via the user terminal 30.

The drone 50 is a mobile body including an autonomous movement controlunit (not shown), an imaging device 51, and a drive system including apropeller 52. The autonomous movement control unit performs varioustypes of control regarding the autonomous movement (autonomous flight)of the drone 50. For example, the autonomous movement control unitexecutes a self-position estimation, an analysis of a surroundingsituation, an action plan using a cost map or the like, the control ofthe drive system, and the like.

The autonomous movement control unit is also capable of controlling animaging operation by the imaging device 51. In this embodiment, theautonomous flight and automatic imaging of the drone 50 are executed onthe basis of the plan information generated by the server apparatus 10.The configuration, method, and the like for implementing the autonomousflight and automatic imaging of the drone 50 are not limited, and anytechnique may be used.

As the imaging device 51, for example, a digital camera including animage sensor such as a complementary metal-oxide semiconductor (CMOS)sensor or a charge coupled device (CCD) sensor is used. In addition, forexample, an infrared camera equipped with an infrared illumination suchas an infrared LED may be used. In this embodiment, the drone 50corresponds to a mobile body having an imaging function. Further, theimaging device 51 corresponds to an imaging unit.

Images captured by the imaging device 51 include both of still imagesand moving images (videos). In the present disclosure, the “image” is aconcept including both of still images and moving images (videos).

In this embodiment, a so-called cloud service is provided by the network35, the server apparatus 10, and the database 5. Thus, it can also besaid that the user terminal 30 is connected to a cloud network.

Note that the method of communicably connecting the server apparatus 10and the user terminal 30 to each other is not limited. For example, theserver apparatus 10 and the user terminal 30 may be connected to eachother using near field communication such as Bluetooth (registeredtrademark) without constructing a cloud network.

FIG. 2 is a flowchart showing the outline of an imaging example usingthe drone imaging system 100.

The user 31 uses the drone imaging system 100 to cause the drone 50 toimage a desired scenery, a building, or the like. For example, anapplication program relating to the drone imaging system 100 is startedby the user 31 via the user terminal 30.

A plan generating graphical user interface (GUI) for generating planinformation is generated by the server apparatus 10 and transmitted tothe user terminal 30. The transmitted plan generating GUI is displayedon the display of the user terminal 30 or the like (Step 101).

In the present disclosure, the plan information is plan informationrelating to the movement and imaging of a mobile body having an imagingfunction within a predetermined region. In this embodiment, the planinformation corresponds to the plan information generated by the serverapparatus 10 and relating to the movement and imaging within apredetermined region on a map. For example, the plan informationincludes various types of information about how to move the drone 50 andhow to cause the drone 50 to perform imaging within a predeterminedregion.

Note that the predetermined region on the map is typically a region inwhich the user 31 flies the drone 50 to perform imaging, and isdesignated by the user 31.

The plan information includes, for example, a transit point (waypoint),a route, a travel time, imaging conditions, an airframe posture, and thelike.

The transit point is a point through which the drone 50 passes, and isdefined by latitude, longitude, or altitude, for example. The traveltime includes a time taken for the drone 50 to pass through a transitpoint, a time taken to travel a route between transit points, and thelike. Absolute time information may be set as the travel time.Alternatively, relative time information based on the timing at whichthe drone 50 starts flight may be set.

The imaging conditions include, for example, an imaging direction, animaging time, and environment information relating to a predeterminedregion. The imaging direction corresponds to the direction of imaging bythe imaging device 51 (imaging optical axis direction), and is definedby the direction of the imaging device 51 based on the airframe posture,for example. Therefore, the airframe posture can also be regarded asinformation included in the imaging conditions.

The environment information is information regarding the surroundingenvironment. For example, the environment information includesinformation such as weather, season, duration of sunshine, brightness,the position of the sun, and the position of the moon. For example, theuser 31 can also generate plan information such as imaging of a sunsetof a sunny day or a winter full moon.

A plan information generating instruction is input via the plangenerating GUI displayed on the user terminal 30 (Step 102). In thisembodiment, the plan information generating instruction input by theuser 31 corresponds to an instruction relating to generation of planinformation relating to movement and imaging of a mobile body having animaging function within a predetermined region.

The server apparatus 10 generates plan information on the basis of theinput plan information generating instruction (Step 103). The generatedplan information is transmitted to the drone 50 (Step 104).

The drone 50 performs autonomous flight and automatic imaging accordingto the plan information generated by the server apparatus 10 (Step 105).

Further, the plan information includes scenario plan information andscanning plan information.

The scenario plan information is plan information relating to movementand imaging within a predetermined region on a map, which is specifiedafter generation of a predicted image or a predicted moving image to bedescribed later. In this embodiment, the drone 50 performs autonomousflight and imaging according to the scenario plan informationtransmitted from the server apparatus 10.

The scanning plan information is plan information generated on the basisof instruction information regarding a scanning range, which will bedescribed later. For example, the scanning plan information includes thearea (volume) and shape of the scanning range that the drone forscanning (hereinafter, referred to as scanning drone 60) scans, and thescanning setting for imaging during scanning or the like. The scanningdrone 60 performs autonomous flight and imaging according to thetransmitted scanning plan information.

Note that the processing from Step 101 to Step 105 described above isalso performed for the generation of the scanning plan informationtransmitted to the scanning drone 60.

FIG. 3 is a block diagram showing a functional configuration example ofthe server apparatus 10 according to this embodiment. FIG. 4 is aschematic diagram showing an example of the plan generating GUI.

The server apparatus 10 includes hardware required for the configurationof a computer, such as a CPU, a ROM, a RAM, and an HDD (see FIG. 15).The CPU loads a program according to the present technology, which isrecorded in advance in the ROM or the like, into the RAM and executesthe program, so that each functional block illustrated in FIG. 3 isimplemented, and an information processing method according to thepresent technology is executed.

For example, the server apparatus 10 can be implemented by any computersuch as a PC. Of course, hardware such as a FPGA or ASIC may be used.Further, in order to implement each block illustrated in FIG. 3,dedicated hardware such as an integrated circuit (IC) may be used.

The program is installed in, for example, the server apparatus 10 viavarious recording media. Alternatively, the program may be installed viathe Internet or the like.

As shown in FIG. 3, the server apparatus 10 includes a communicationcontrol unit 11, a GUI generation unit 12, and a scenario planinformation generation unit 13.

The communication control unit 11 controls communication with the userterminal 30 and the drone 50. For example, the communication controlunit 11 receives an instruction to generate scenario plan informationinput via the user terminal 30, and supplies the received instruction tothe GUI generation unit 12 and the scenario plan information generationunit 13. Further, the scenario plan information generated by thescenario plan information generation unit 13 is transmitted to the drone50.

In this embodiment, the communication control unit 11 functions as acontrol unit that controls the operation relating to the movement andimaging of the mobile body having an imaging function on the basis ofthe scenario plan information. In other words, the transmission of thescenario plan information to the drone 50 controls the autonomous flightand automatic imaging of the drone 50.

The present technology is not limited to the above, and the serverapparatus 10 may remotely control the autonomous flight and automaticimaging of the drone 50 in real time. In this case, a block of remotelycontrolling the drone 50 functions as a control unit.

The GUI generation unit 12 includes a map data acquisition unit 14, amap image generation unit 15, a timeline generation unit 16, aninstruction information acquisition unit 17, an image data acquisitionunit 18, a predicted-image generation unit 19, and an image datatransmission unit 20. Note that a map data DB 24 and an image data DB 25are constructed in the database 5 shown in FIG. 1.

The blocks included in the GUI generation unit 12 cooperate with eachother to generate a plan generating GUI 110 illustrated in FIG. 4.

In this embodiment, the plan generating GUI 110 includes a map displaypart 111, an imaging condition setting part 112, a timeline display part113, a predicted-image display part 114, a preview setting button 115, amoving-image preview button 116, a scenario execution button 117, anopen button 126, and a save button 127.

A map including buildings, roads, and the like is displayed in the mapdisplay part 111. Note that FIG. 4 shows transit points included in thescenario plan information and a route connecting the transit points, andomits the illustration relating to the map such as a road and a map.Note that a mode in which both a map and a transit point are displayed,a mode in which only a map is displayed, and a mode in which only atransit point is displayed may be switchable according to an instructionfrom the user 31.

The user 31 designates a map to be displayed in the map display part111. For example, a map including a region desired to be imaged by thedrone 50 is designated. The method of designating a map is not limited.For example, a map is displayed on the basis of input of an address, anda map including a region desired to be imaged is then displayed in themap display part 111 by a scroll operation, an enlargement/reductionoperation, or the like.

Alternatively, the user 31 may designate a particular building,mountain, lake, etc. (hereinafter, referred to as a landmark). Inresponse to an instruction to designate a particular landmark, the mapincluding the landmark is displayed in the map display part 111. Ofcourse, the present technology is not limited to those methods, and anyother method may be employed.

In this embodiment, the landmark corresponds to an object present in apredetermined region. Further, the region desired to be imagedcorresponds to a predetermined region on the map. Typically, the entireregion displayed in the map display part 111 is set as a region desiredto be imaged.

The instruction information acquisition unit 17 shown in FIG. 3 acquiresinstruction information relating to various instructions that are inputfrom the user 31 via the plan generating GUI 110. The instructionrelating to the display of the map in the map display part 111(instruction information) is output to the map data acquisition unit 14.

The map data acquisition unit 14 acquires the map data from the map dataDB 24 on the basis of the instruction information. For example, the mapdata DB 24 stores various types of map data. For example, landmarkinformation and latitude and longitude information are stored inassociation with each other. This makes it possible to acquire map dataincluding the landmark in response to the designation of the landmark.

On the basis of the map data acquired by the map data acquisition unit14, the map image generation unit 15 generates image data of a map to bedisplayed in the map display part 111 of the plan generating GUI 110.For example, a display region, a magnification, the presence or absenceof display of a landmark, and the like are appropriately set.

The image data generated by the map image generation unit 15 istransmitted to the user terminal 30 by the image data transmission unit20. Thus, the map is displayed in the map display part 111 of the plangenerating GUI 110. Further, the display of the map is updatedappropriately in response to the user's operation of scrolling the map,for example.

Further, in this embodiment, as shown in FIG. 4, any point in the mapdisplayed in the map display part 111 is selectable by the user 31. Theselected point is set as a transit point 121 and is identifiablydisplayed. A plurality of transit points 121 is connected to each otherto generate a moving route 122 of the drone 50.

As described above, in this embodiment, a position in the map (regiondesired to be imaged) can be indicated via the plan generating GUI 110.

The indication of the transit point 121 can be input by moving a pointerover the map and selecting a decision button. Alternatively, thelatitude and longitude may be input. Alternatively, the transit point121 can also be indicated by selecting a predetermined landmark on themap.

For example, if the Tokyo Tower is selected as the landmark, a pointwhere the Tokyo Tower exists (a point of the latitude and longitude ofthe Tokyo Tower) is designated as the transit point 121. Of course, apoint in the vicinity of the Tokyo Tower may be designated as thetransit point 121 in response to the selection of the Tokyo Tower.

Further, the method of generating the moving route 122 of the drone 50is not limited. For example, the transit points selected by the user 31may be connected to each order in the selected order. Further, when thedrone 50 fails to move in accordance with the moving route 122 displayedin the map display part 111 due to a building or the like, the fact thatthe moving route 122 cannot be generated may be displayed.

In this embodiment, the map image generation unit 15 generates imagedata including the transit point 121 and the moving route 122 on thebasis of the instruction information to designate the transit point 121.Of course, an image of the transit point 121 and the moving route 122may be generated and superimposed on the map by a block different fromthe map image generation unit 15.

The imaging condition setting part 112 shown in FIG. 4 is a GUI forsetting the imaging conditions. In this embodiment, the imagingconditions are set for each transit point 121. In other words, it ispossible to input an instruction relating to what kind of imaging is tobe executed by the drone 50 that has reached the transit point 121. Ofcourse, it is also possible to cause the drone 50 traveling along themoving route to perform imaging.

As shown in FIG. 4, in this embodiment, it is possible to input thealtitude (m), the airframe posture (degrees), and the camera direction(roll angle, pitch angle, and yaw angle).

For example, the altitude can be set as the distance to the ground. Theairframe posture can be set as an angle inclined as a yaw angle in apredetermined direction on the basis of a state of the drone 50installed on the ground or a predetermined direction. Further, forexample, for the camera direction, the roll angle, the pitch angle, andthe yaw angle can be set with reference to the front direction of thedrone 50. Note that the airframe posture and the coordinate system fordefining the camera direction may be arbitrarily set. For example, thecoordinate system is set on the basis of the installation state of thedrone 50 before the flight. Of course, the present technology is notlimited to the above. Further, the camera direction corresponds to theimaging direction.

It is also possible to designate other parameters by scrolling down theimaging condition setting part 112 illustrated in FIG. 4. For example,various imaging conditions and various parameters relating to autonomousflight, such as an imaging time, environment information, a movementspeed, the time to start movement, and the time to end movement, can beset.

Note that a transit point 123 for which the imaging conditions are to beset is displayed so as to be distinguishable from other transit points.For example, in the example shown in FIG. 4, the transit point 123 forwhich the imaging conditions are to be set is displayed by a star mark.Of course, the present technology is not limited to such a display mode.

The predicted-image display part 114 displays a predicted image 124 thatis predicted to be acquired when imaging is performed by the drone 50.The display of the predicted image 124 can also be referred to aspreview display of an image that is predicted to be acquired whenimaging is performed by the drone 50. Further, the predicted image 124can also be referred to as a simulated image when the drone 50 performsimaging.

The instruction information acquisition unit 17 shown in FIG. 3 acquiresthe instruction information regarding the selection of the transit point121 and the instruction information regarding the designation of theimaging conditions for each transit point 121, and outputs theinstruction information to the image data acquisition unit 18.

On the basis of the instruction information, the image data acquisitionunit 18 acquires image data relating to a predetermined region on a mapfrom the image data DB 25. In this embodiment, the image data of a map(region desired to be imaged) designated by the user 31 is acquired.Note that in this embodiment the image data acquisition unit 18corresponds to an acquisition unit that acquires image data relating toa predetermined region on a map.

The image data DB 25 stores image data relating to various regions andvarious landmarks on the map.

For example, the image data of an omnidirectional image, which isacquired when the drone including a 360-degree camera or the likeperforms imaging while scanning a region on the map, is stored. In otherwords, a scanning mobile body having an imaging function may performimaging while scanning a predetermined region, and thus the image datamay be acquired. Of course, captured image data other than theomnidirectional image data may be used.

Alternatively, a virtual image such as a 3D polygon may be used as theimage data. For example, a virtual image in which a building, alandscape, or the like included in a predetermined region is viewed fromany coordinates or altitude and in any direction may be held as theimage data.

The method of acquiring the map data stored in the map data DB 24 shownin FIG. 3 and the image data stored in the image data DB 25, the dataformat thereof, or the like is not limited. For example, the map dataand the image data may be acquired via the network 35.

In this embodiment, the image data corresponds to image data relating toa predetermined region on the map.

The predicted-image generation unit 19 generates a predicted image 124on the basis of the image data acquired by the image data acquisitionunit 18.

The predicted-image generation unit 19 generates a predicted image 124on the basis of the transit point 123 and the imaging conditionsincluded in the instruction information. For example, a predicted imagethat is predicted to be acquired when the drone 50 actually performsimaging is generated on the basis of the latitude, longitude, andaltitude of the transit point 123 and the imaging direction.

In addition, the method of generating the predicted image 124 is notlimited, and any method may be employed. For example, if there is animage captured from the transit point 123 by the scanning drone, thepredicted image 124 is generated on the basis of such an image. Forexample, an image captured by the scanning drone may be used as thepredicted image 124 as it is.

If the scanning drone does not perform imaging from the transit point123 designated by the user 31, for example, the predicted image 124 canalso be generated on the basis of a plurality of images captured fromperipheral points. For example, the predicted image 124 can be generatedfrom peripheral images by using a free-viewpoint video technique or thelike. As a result, it is possible to generate a high-accuracy predictedimage 124 and to generate high-quality plan information.

Alternatively, if the scanning drone does not perform imaging from thetransit point 123 designated by the user 31, the predicted image 124 isgenerated on the basis of an image captured from the point closest to atransit point. In other words, an image that is included in the imagedata and would be closest is selected as the predicted image 124. Thismakes it possible to reduce the processing load and speed up theprocessing.

In addition, any machine learning algorithm using, for example, a deepneural network (DNN) may be used. For example, the use of artificialintelligence (AI) or the like for performing deep learning allows animprovement in the generation accuracy of the predicted image 124. Notethat the machine learning may be similarly applied to various othertechniques within the present disclosure.

The image data of the predicted image 124 generated by thepredicted-image generation unit 19 is transmitted to the user terminal30 by the image data transmission unit 20. Thus, the predicted image 124is displayed in the predicted-image display part 114 of the plangenerating GUI 110. In addition, the display of the predicted image 124is appropriately updated in response to an instruction to switch thetransit point 123, an instruction to change the imaging conditions, orthe like, which is given by the user.

As described above, in this embodiment, the predicted image 124 ispresented on the basis of an instruction relating to the generation ofthe scenario plan information relating to the movement and imaging ofthe mobile body having an imaging function within a predetermined regionon the map. Specifically, the plan generating GUI including thepredicted image 124 is output so as to input an instruction to generatethe scenario plan information. In other words, the output of the plangenerating GUI is included in the presentation of the predicted image124.

In this embodiment, the GUI generation unit 12 corresponds to apresentation unit that presents a predicted image on the basis of aninstruction relating to generation of plan information relating to themovement and imaging of a mobile body having an imaging function withina predetermined region. Further, the predicted-image generation unit 19corresponds to an image generation unit that generates, on the basis ofthe image data, a predicted image predicted to be acquired when theimaging is performed in a predetermined region.

The timeline display part 113 displays changes of predeterminedparameters along a time series from the start of flight to the end offlight of the drone 50. For example, the changes along a time series ofthe imaging conditions such as the altitude, the airframe posture, andthe camera direction of the drone 50 are displayed as a timeline on thebasis of a predetermined time unit. The timeline display part 113 alsodisplays time information when the drone 50 reaches each transit point121.

For the time information displayed in the timeline, absolute timeinformation may be used, or relative time information based on the timeat which the drone 50 starts autonomous flight according to the scenarioplan information may be displayed.

As shown in FIG. 4, by scrolling the timeline display part 113 in thehorizontal direction, it is possible to confirm the imaging conditionsin a desired time zone. Further, by scrolling the timeline display part113 in the vertical direction, it is possible to confirm changes ofvarious parameters along a time series.

The instruction information acquisition unit 17 shown in FIG. 3 acquiresthe instruction information regarding the selection of the transit point123 and the instruction information regarding the designation of theimaging conditions for each transit point 123, and outputs theinstruction information to the timeline generation unit 16.

The timeline generation unit 16 generates image data of the timeline onthe basis of the instruction information.

The image data of the timeline generated by the timeline generation unit16 is transmitted to the user terminal 30 by the image data transmissionunit 20. Thus, the timeline is displayed in the timeline display part113 of the plan generating GUI 110. In addition, the display of thetimeline is appropriately updated in response to an instruction toswitch the transit point 123, an instruction to change the imagingconditions, or the like, which is given by the user 31.

The preview setting button 115 is a button for performing varioussettings relating to the display (preview display) of the predictedimage displayed in the predicted-image display part 114. When thepreview setting button 115 is selected by the user 31, a predeterminedscreen opens, and various settings relating to the predicted image 124can be changed.

Examples of the display settings of the predicted image include thesettings of the accuracy of the predicted image 124, the processing ofthe predicted image, and frames per second (FPS) of the moving imagedisplayed as the predicted image.

As for the accuracy of the predicted image, for example, a high-accuracymode in which the predicted image 124 has high accuracy and alow-accuracy mode in which the predicted image 124 has low accuracy canbe set to be switchable.

For example, it is possible to generate the predicted image 124 withvery high accuracy by executing the above-mentioned free-viewpoint videotechnique, machine learning, or the like. On the other hand, it ispossible to display the predicted image 124 with a low processing loadand at high speed, though the accuracy is reduced, by selecting an imagecaptured from a point closest to the transit point 123 as the predictedimage 124.

For example, if the high-accuracy mode is set, a time lag may occur inthe display of the predicted image 124. Thus, the two modes in which theaccuracy of the predicted images 124 differs are configured to beswitchable on the plan generating GUI 110, so that the operability canbe improved.

As for the processing of the predicted image, in this embodiment, thepredicted image is processed by the predicted-image generation unit 19illustrated in FIG. 3 on the basis of at least one of the imagingdirection, the imaging time, or the environment information relating toa predetermined region when the drone 50 performs imaging.

For example, the predicted image is subjected to image processing filteron the basis of time-varying elements such as the sun, the moon,brightness, and weather. For example, when the brightness is low(nighttime, cloudiness, etc.) among the time zones imaged by the drone50, image processing is performed such that the brightness of thepredicted image is reduced. Note that the time-varying elements such asthe sun, the month, brightness, and weather are information included inthe environment information regarding the imaging environment.

Note that the type of the image processing filter or the like is notlimited. For example, it may be designated by the user on the plangenerating GUI 110. In addition, for the weather or the like, thelatitude, the longitude, and the time may be acquired from a web serviceor the like. Further, the method of processing the predicted image isnot limited, and machine learning or the like may be used. Further, theprocessing also includes temporally connecting a plurality of predictedimages to form a moving image on the basis of an instruction from theuser 31.

As for the setting of the FPS of the moving image, if the predictedimage is displayed as a moving image, any frame rate can be selected bythe user 31. For example, when it is desired to reduce the amount ofdata, it is possible to perform a setting for decreasing the frame rate.

The moving-image preview button 116 is a button for displaying thepredicted image 124, which is displayed in the predicted-image displaypart 114, as a moving image (a predicted image displayed as a movingimage may be referred to as a predicted moving image).

When the user 31 selects the moving-image preview button 116, apredicted moving image is displayed on the basis of the moving route andthe imaging conditions set by the user 31. For example, when the imagingconditions at each point of the drone 50 moving in the moving route 122are set, a predicted image of each point of the drone 50 is generated.The generated predicted images are arranged in the imaging order, sothat a predicted moving image is generated.

Of course, in the case where an instruction to capture a moving image isinput at each transit point, the predicted images 124 at respectivetransit points may be continuously synthesized and displayed as apredicted moving image.

The scenario execution button 117 is a button for causing the drone 50to execute the moving route and the imaging conditions set by the user31. When the scenario execution button 117 is selected, the scenarioplan information input so far is determined.

In other words, the plan information regarding the movement and imagingof the drone 50 within a predetermined region on the map, which isspecified after the generation of the predicted image 124 or thepredicted moving image, is determined.

The plan generating GUI 110 also includes the save button 127 capable ofstoring the generated scenario plan information and the open button 126capable of displaying the saved scenario plan information. This makes itpossible to save and redisplay the scenario plan information in theprocess of generation, for example.

A plan generation unit 21 shown in FIG. 3 generates scenario planinformation in response to the selection of the scenario executionbutton 117. The generated scenario plan information is held by a planholding unit 22 and stored in the database 5. Note that the number ofpieces of scenario plan information to be held, a saving period, and thelike are not limited.

When the open button 126 shown in FIG. 4 is selected, the scenario planinformation is read from the database 5 and transmitted to the userterminal 30. Subsequently, for example, the scenario plan information inthe process of generation is expanded to the user terminal 30.

FIG. 5 is a flowchart showing a specific example of processing forgenerating the scenario plan information.

The map designated by the user 31 is displayed in the map display part111 of the plan generating GUI 110 (Step 201). The user 31 selects anypoint from the map displayed in the map display part 111. Further, theuser 31 sets the imaging conditions regarding each selected point viathe imaging condition setting part 112.

A predicted image is generated on the basis of the imaging conditions ofeach transit point designated by the user 31. As a result, a predictedimage based on the scenario plan information set by the user 31 isdisplayed in the predicted-image display part 114 (Step 202).

If the user 31 changes the display setting of the predicted image by thepreview setting button 115 (YES in Step 203), the predicted image isprocessed on the basis of the display setting of the predicted image(Step 204). In other words, if the user 31 selects the preview settingbutton 115 and changes the setting, the processed predicted image 124 isdisplayed in the predicted-image display part 114.

If the user 31 changes the setting of the predicted image 124 by thepreview setting button 115, the processed predicted image 124 isdisplayed by the preview setting button 115 (Step 205). Of course, ifthe setting of the predicted image 124 is not changed (NO in Step 203),the display state of the predicted image is maintained. If the user 31selects the scenario execution button 117 (Step 206), the plangeneration unit 21 generates the scenario plan information (Step 207).

FIG. 6 is a block diagram showing a functional configuration examples ofthe scanning drone 60 and a server apparatus 80. FIG. 7 is a schematicdiagram showing a scanning plan generating GUI 130 for executingscanning of the scanning drone 60. Note that in this embodiment thescanning drone 60 corresponds to a mobile body for scanning having animaging function.

The scanning drone 60 includes a power unit 61, a sensor group 62, acamera 63, an airframe control unit 64, an obstacle detection unit 65, amobile body information calculation unit 66, an image data recordingunit 67, an action planning unit 68, a cost map generation unit 69, anda communication control unit 70.

The power unit 61 includes various devices relating to a drive systemfor moving the scanning drone 60. For example, the power unit 61includes a servo motor capable of specifying torque, a motion controllerthat decomposes and replaces the motion of the movement of the scanningdrone 60, and a feedback controller by a sensor in each motor.

For example, the power unit 61 also includes a motor including four tosix propellers facing upward of the airframe, and a motion controllerthat decomposes and replaces the motion of the movement of the scanningdrone 60 to and with the rotation amount of each motor.

The sensor group 62 includes various sensors for detecting external andinternal information of the scanning drone 60 and the self-position ofthe scanning drone 60. Specifically, for example, the sensor group 62includes a global positioning system (GPS) for detecting theself-position, a magnetic sensor for measuring the posture of thescanning drone 60, an inertial measuring device (IMU), and the like.

For example, the sensor group 62 includes a laser ranging sensor fordetecting an obstacle or the like, a contact sensor, an ultrasonicsensor, a radar, LiDAR (Light Detection and Ranging, Laser ImagingDetection and Ranging), a barometer for measuring the atmosphericpressure, and the like.

The camera 63 images the periphery of the scanning drone 60 and acquiresimage data. In this embodiment, the camera 63 is an omnidirectionalcamera capable of simultaneously imaging at 360 degrees around, andcaptures an image within a region designated by the user 31. In otherwords, in this embodiment, the image data is an omnidirectional image.However, the image data may be a general planar image.

Note that the type of the camera 63 is not limited. For example, adigital camera including an image sensor such as a CMOS sensor or a CCDsensor may be used. The camera 63 may function as the sensor group 62.For example, in addition to a camera capable of simultaneously imagingat 360 degrees around, a stereo camera or the like for detecting anobstacle may function as the sensor group 62.

The airframe control unit 64 performs control of the operation of thescanning drone 60 on the basis of the action plan supplied from theaction planning unit 68. For example, when the power unit 61 operates onthe basis of the control signal, the scanning drone 60 is moved. In thisembodiment, the power unit 61 (airframe control unit 64) implements amoving mechanism capable of moving in a predetermined region.

The obstacle detection unit 65 detects an obstacle that hinders themovement of the scanning drone 60 on the basis of data or signals fromthe sensor group 62. For example, the obstacle corresponds to a buildingor the like that blocks the moving route of the scanning planinformation of the scanning drone 60.

The mobile body information calculation unit 66 calculates the state ofthe scanning drone 60 on the basis of the data or signals from thesensor group 62. For example, the self-position and the airframe postureof the scanning drone 60 are calculated as the mobile body information.In addition, the speed, acceleration, presence or absence and contentsof an abnormality of the scanning drone 60, the other states of thedevices mounted on the scanning drone 60, and the like are calculated.

The image data recording unit 67 records image data captured by thecamera 63. In this embodiment, the latitude and longitude, the altitude,and the airframe posture at each time of the scanning drone 60, whichare supplied from the mobile body information calculation unit 66, arerecorded to be linked to the image data. Further, the image datarecording unit 67 transmits the image data to the server apparatus 80via the communication control unit 70. Note that the timing at which theimage data is transmitted is not limited. For example, the image datamay be transmitted in real time at the time when the image data isacquired, or may be transmitted collectively after the scanning iscompleted.

The action planning unit 68 makes an action plan of the scanning drone60 for scanning on the basis of information supplied from the cost mapgeneration unit 69 and the communication control unit 70. For example,the action planning unit 68 performs planning such as settings relatingto starting, stopping, traveling direction (e.g., forward, backward,left, right, or change of direction), moving speed, and imaging. Theaction plan also includes scanning plan information. In other words, theaction plan includes autonomous flight, such as avoidance of obstacles,of the scanning drone 60, and movement and imaging to perform scanningwithin a predetermined region.

More specifically, the action planning unit 68 makes an action plan onthe basis of the scanning range, the imaging density, the imaginginterval, the cost map, and the like instructed by the user 31. Forexample, when the time of the scanning is set long with respect to thevolume (area) of the scanning range, the scanning interval of thescanning drone 60 within the scanning range becomes dense.

In this embodiment, the scanning range includes at least one of theshape information such as a rectangular parallelepiped or a sphere, theposition information such as latitude, longitude, and altitude, or thescale information such as volume and area.

For example, when the scanning range is set to be spherical, thescanning range having a predetermined radius around the position of thecenter of gravity of the spherical shape is defined.

Note that the setting of the scanning range is not limited. For example,the center of gravity, the rotation angle, or the like according to theshape of the scanning range may be set. In this embodiment, the actionplan includes the scanning range, the settings relating to scanning, anda moving route.

Note that a specific algorithm or the like for generating the actionplan is not limited. For example, the action plan may be generated by anA* algorithm (A star search algorithm) of dividing an environment intogrids and optimizing the arrival determination and the weight of theroute to generate the best path, the Dijkstra's algorithm (Dijkstramethod) of obtaining the shortest route between two vertices on a graph,a rapidly-exploring random tree (RRT) algorithm of extending the pathfrom the self-location to the incrementally reachable location whileappropriately pruning the path, or the like.

The cost map generation unit 69 generates a cost map on the basis of theinformation from the obstacle detection unit 65 and the mobile bodyinformation calculation unit 66. In this embodiment, a cost map isgenerated on the basis of information of an obstacle or the like thatblocks the route of the scanning drone 60, and the self-position andposture of the scanning drone 60.

The communication control unit 70 communicates with a communicationcontrol unit 90 that allows communication with the server apparatus 80.Note that the method of communicably connecting the communicationcontrol units 70 (90) to each other is not limited. For example, anynetwork such as a WAN or LAN is used. The communication control unit 70(90) is capable of transmitting and receiving various types ofinformation (data) by controlling the communication device such as amodule for establishing communication or a router.

The server apparatus 80 includes a GUI generation unit 81 and a scanningplan information unit 82. The GUI generation unit 81 includes a map dataacquisition unit 83, a map image generation unit 84, a scanning rangesetting unit 86, an instruction information acquisition unit 85, ascanning time prediction unit 87, an image data holding unit 88, animage data transmission unit 89, and the communication control unit 90.The scanning plan information unit 82 includes a scanning plangeneration unit 91 and a scanning plan holding unit 92.

Note that the map data acquisition unit 83, the map image generationunit 84, and the image data transmission unit 89 have the same functionsas those of the first embodiment. Further, the communication controlunit 90 has the same function as that of the communication control unit70. The server apparatus 80 includes the map data DB 24 of the serverapparatus 10.

As shown in FIG. 7, the scanning plan generating GUI 130 includes themap display part 111 of the plan generating GUI 110, a scanning rangedisplay part 132, a scanning time display part 133, a scanning settingdisplay part 134, and a scanning execution part 135.

The instruction information acquisition unit 85 shown in FIG. 6 outputsinstruction information relating to the scanning range of the scanningdrone 60 to the scanning range setting unit 86. In other words, thescanning plan information of the scanning drone 60 is generated on thebasis of the instruction information relating to the scanning range.

The scanning range setting unit 86 sets the scanning range of thescanning drone 60 on the basis of the instruction information relatingto the scanning range. In this embodiment, the volume (area), shape, andthe like of a scanning range 136 can be set. For example, the user 31can set the scanning range 136 to a variety of shapes such as a hexagon,a circle, and a square. In this embodiment, the scanning range 136 mayalso be determined as a linear shape in addition to the scanning range136 determined as a region.

The image data of the scanning range set by the scanning range settingunit 86 is transmitted to the user terminal 30 by the image datatransmission unit 89. As a result, the scanning range 136 is displayedin the scanning range display part 132 of the scanning plan generatingGUI 130.

Note that the method of determining the scanning range 136 is notlimited. For example, a predetermined shape displayed in an areaselection display part 137 may be selected, or the user 31 may freelydetermine the scanning range 136. Further, a scanning range 136 having apredetermined radius about the landmark may be determined, for example,when a particular landmark is selected.

Note that in this embodiment the instruction information acquisitionunit 85 and the scanning range setting unit 86 correspond to a scanninggeneration unit that generates scanning plan information relating toscanning and imaging of the scanning mobile body within a predeterminedregion.

The instruction information acquisition unit 85 shown in FIG. 6 acquiresthe instruction information relating to the scanning range and outputsthe instruction information to the scanning time prediction unit 87.

The scanning time prediction unit 87 predicts the time actually takenfor scanning on the basis of the instruction information relating to thescanning range. Typically, a necessary time is determined on the basisof the size of the scanning range 136, the speed at which the scanningdrone 60 moves, and the like. Of course, the necessary time may bepredetermined, and the settings for scanning may be determined on thebasis of the necessary time.

The image data of the time actually taken for the scanning predicted bythe scanning time prediction unit 87 is transmitted to the user terminal30 by the image data transmission unit 89. As a result, the timeactually taken for scanning is displayed in the scanning time displaypart 133 of the scanning plan generating GUI 130.

The scanning setting display part 134 is a GUI for setting scanning. Inthis embodiment, according to the instruction of the user 31, it ispossible to set the imaging density of the camera 63 of the scanningdrone 60, the time and the route for scanning of the scanning drone 60,and the like.

For example, the imaging density indicates how much time scanning isperformed on the volume (area) of the scanning range 136. In otherwords, (the volume of the scanning range 136)/(the time to scan)=theimaging density. Further, for example, the imaging density indicateswhether or not imaging is performed in accordance with the distancetraveled by the scanning drone 60. For example, the following settingmay be made: the scanning drone 60 performs imaging once every threemeters.

The image data holding unit 88 holds the image data transmitted from theimage data recording unit 67 via the communication control unit 90. Theheld image data is acquired by an image data acquisition unit (notshown), and is generated as a predicted image by a predicted-imagegeneration unit (not shown).

In this embodiment, the omnidirectional image acquired by the camera 63is held. Thus, the predicted-image generation unit cuts off a portioncorresponding to the field angle of the camera 63 from the image data onthe basis of the imaging direction of the camera 63 and the airframeposture of the scanning drone 60. Lens curvature (distortion) correctionis performed on the cut image data, and thus a predicted image isgenerated.

The scanning plan generation unit 91 shown in FIG. 6 generates scanningplan information in accordance with the selection of the scanningexecution unit 135. The generated scanning plan information is held bythe scan plan holding unit 92 and stored in the database 5. Note thatthe number of pieces of scanning plan information to be held, a savingperiod, and the like are not limited.

FIG. 8 is a schematic diagram showing a specific example of the scanningof the scanning drone 60. FIG. 8A is a schematic diagram showing anexemplary moving route scanned by the scanning drone 60. FIG. 8B is aschematic diagram showing an exemplary method of calculating a movingroute of the scanning drone 60.

As shown in FIG. 8A, a scanning range 140 is determined by aninstruction from the user 31. At this time, a moving route 141 forperforming scanning by the scanning drone 60 is determined on the basisof the setting of the imaging density or the like determined by the user31.

As shown in FIG. 8A, when there is no obstacle within the scanning range140, the action planning unit 68 plans the moving route 141 such thatthe image data within the scanning range 140 can be sufficientlyacquired. For example, the moving route 141 is set to be wavy on thesurface of the scanning range 140 having a constant altitude. Further,after the surface of the scanning range 140 is scanned, the moving route141 is set so as to change the altitude by a certain distance andfurther perform scanning in a wavy manner.

For example, when the height of the scanning range 140 is set to 50 m,the moving route 141 may be set for each height of 10 m. In other words,the scanning drone 60 scans the scanning range 140 five times atdifferent heights.

Note that the method of setting the moving route 141 is not limited. Forexample, the interval of the moving route may be set on the basis of theperformance such as the imaging range of the camera 63 of the scanningdrone 60. Further, for example, the user 31 may determine predeterminedpositions within the scanning range, and the moving route 141 may be setso as to connect such positions.

As shown in FIG. 8B, the cost map generation unit 69 generates a costmap 143 for the moving route 142 on which the scanning drone 60 hasmoved. In this embodiment, the cost around the route through which thescanning drone 60 has passed once is set high by the cost map generationunit 69. For example, as the radius becomes shorter in a circle aroundthe moving route 142, the cost is set higher. In other words, the costmap generation unit 69 generates a three-dimensional cylindrical costmap 143 around the route through which the scanning drone 60 has passed.Not that in this embodiment the cost map 143 corresponds to costinformation relating to a scanning route.

In addition, when an obstacle 144 is present on the moving route 142 bythe obstacle detection unit 65, the cost map generation unit 69 sets thecost around the obstacle 144 to be high. In other words, a moving route145 is generated such that the scanning drone 60 avoids the obstacle144.

The action planning unit 68 generates the next moving route 147 of thescanning drone 60 on the basis of the cost map generated by the cost mapgeneration unit 69 such that the cost is reduced. In other words, inthis embodiment, the moving route 147 is generated so as not to overlapa moving route 146 having a different height (Z-axis) when viewed fromthe height direction (Z-axis direction).

Note that the method of generating the cost map is not limited. Forexample, the cost map may be generated by a route search algorithm suchas an A star search algorithm or the Dijkstra method. Any machinelearning algorithm may also be used. Further, the cost map generatedonce may be updated at any time.

This makes it possible to uniformly scan the scanning range of thethree-dimensional space by increasing the cost of the route that hasbeen taken before. In this embodiment, the moving route 145 correspondsto a scanning route that has been taken in the past.

As described above, in the server apparatus 10 according to thisembodiment, the image data relating to a region on a map desired to beimaged is acquired. The predicted image 124, which is predicted to beacquired when imaging is performed within a region desired to be imaged,is generated on the basis of the image data. The predicted image 124 ispresented on the basis of an instruction relating to the generation ofscenario plan information relating to movement and imaging of a drone 50having an imaging function within a region desired to be imaged. Thus,it is possible to generate high-quality plan information for themovement and imaging of the mobile body having an imaging function.

In the case of imaging using a drone, it is difficult to imagine inadvance what field angle and flow a video to be captured will have, evenif a moving route is designated in advance. So, imaging performed usinga drone strongly depends on manual scanning by a human.

For example, imaging is performed in a system of two persons having arole of operating a camera of a drone and a role of operating the drone.Further, when the camera and the drone are operated by one person, theoperation is difficult and a video cannot be taken well.

On the other hand, the autonomous flight technology for a drone thatautomatically flies along a route designated in advance by a user isbecoming easier.

So, in this technology, at the stage of generating a moving route, themoving route and the direction of the camera are designated whileconfirming the image data predicted to be imaged from the moving routeand the direction of the camera in each moving route, so that imaging byautonomous flight is achieved.

This makes it possible to easily capture a video desired to be capturedeven without the sophisticated operation technology of the drone.Further, it is possible to reduce the number of times of trial and errorin imaging, and to reduce the cost.

Second Embodiment

A drone imaging system 200 according to a second embodiment of thepresent technology will be described. In the following description,descriptions of a configuration and an operation similar to those of thedrone imaging system 100 described in the above embodiment are omittedor simplified.

In the first embodiment, the predicted image of the transit point 121selected by the user is displayed when the scenario plan information isgenerated. In the second embodiment, the user selects a landmarkdisplayed in the map display part, and thus the predicted image can bedisplayed.

FIG. 9 is a block diagram showing a functional configuration example ofa server apparatus 150 according to the second embodiment of the presenttechnology. A GUI generation unit 151 of the server apparatus 150includes a candidate point generation unit 153 and a candidate imagegeneration unit 154 in addition to the GUI generation unit 12 of theserver apparatus 10.

Further, in the server apparatus 150, an imaging rule DB 155 is added asan example of the database 5 in addition to the map data DB 24 and theimage data DB 25. Note that a scenario plan information generation unitis similar to the scenario plan information generation unit 13 of thefirst embodiment, and thus the illustration thereof is omitted.

FIG. 10 is a schematic diagram showing an example of a plan generatingGUI 160 when a candidate image is used. As shown in FIG. 10, the plangenerating GUI 160 includes the map display part 111, the timelinedisplay part 113, the moving-image preview button 116, the scenarioexecution button 117, the open button 126, and the save button 127 ofthe plan generating GUI 110. In addition to those above, the plangenerating GUI 160 includes a landmark information display part 162, acandidate image generation part 163, a candidate image display part 164,and a candidate image addition part 165.

FIG. 11 is a flowchart showing a specific example of processing forgenerating scenario plan information using a candidate image. Theprocessing of Step 301, Step 306, and Step 307 are the same as in thefirst embodiment, and thus description thereof is omitted.

As shown in FIG. 10, the user selects a particular landmark on the mapdisplayed in the map display part 111 (Step 302). Information of theselected landmark is displayed in the landmark information display part162. Note that in the second embodiment a schematic diagram 170representing the selected landmark is displayed in the map display part111. For example, when the user selects the Tokyo Tower as a landmark,the schematic diagram 170 is displayed in a diagram simulating the TokyoTower in the vicinity of the selected transit point 171 (asterisk).

The instruction information acquisition unit 152 shown in FIG. 9acquires instruction information relating to the selection of thetransit point 171, and outputs the instruction information to thecandidate point generation unit 153.

The candidate point generation unit 153 generates a candidate point ofthe landmark selected by the user on the basis of the imaging rules heldin the imaging rule DB 155.

The candidate point indicates the position information set for eachlandmark selected by the user. For example, position information such asa position 30 m away from the Tokyo Tower in the directions of north,south, east, and west is set for each landmark.

Note that in this embodiment the candidate point indicates at least oneof a relative imaging position of the drone 50 set for eachclassification of the landmark serving as a selection target or adisplay state of the landmark in the acquired image.

The landmark information display part 162 displays information regardingthe landmark held in the imaging rule DB 155. For example, the name ofthe landmark selected by the user, the latitude and longitude, the typeof the building, and the like are displayed. The present technology isnot limited to the above, and a height or the like may be displayed aslong as it is a mountain or a building.

The candidate image automatic generation button 163 is a button forgenerating a candidate image of a landmark that the user makes aselection target. In this embodiment, landmark candidate images 176 and177 and the like are generated on the basis of the imaging rules set forthe selected landmark (Step 303).

Note that in this embodiment the candidate image corresponds to aprediction candidate image generated on the basis of the positioninformation of the object serving as the selection target.

The candidate image generation unit 154 generates a candidate image whenimaging is performed by the drone 50 on the basis of the generatedcandidate point.

The candidate image generation unit 154 generates image data of thecandidate image. The image data of the candidate image generated by thecandidate image generation unit 154 is transmitted to the user terminal30 by the image data transmission unit 20. Thus, the candidate images176 and 177 are displayed in the candidate image display part 164 of theplan generating GUI 160 (Step 304).

In this embodiment, the user can select the generated candidate images176 and 177 on the basis of the imaging rules. The user can also selectanother candidate image by scrolling the candidate image display part164 downward.

In the imaging rule DB 155, the imaging rules relating to imaging ofvarious landmarks are held. An example of the imaging rules will bedescribed with reference to FIG. 12.

The candidate image addition button 165 is a button for adding thecandidate image of the landmark selected by the user to the movingroute. In other words, the position of the transit point 171 linked tothe candidate image selected by the user and the imaging rules are addedto the scenario plan information (Step 305).

For example, as shown in FIG. 10, when the candidate image addition part165 is selected by the user, broken lines 174 connecting the transitpoint 171 and the transit points 172 and 173 are displayed in the mapdisplay part 111. In other words, a moving route (broken lines 174 andsolid line 175) that passes through the transit point 171 is generatedas scenario plan information of the drone 50.

In other words, a plurality of candidate images displayed in thecandidate image display part 164 can also be referred to as predictedimages. Further, the position of the transit point linked to thecandidate image and the imaging rules can also be referred to as planinformation regarding the movement and imaging within a predeterminedregion on the map, which is specified after the generation of thepredicted image. A candidate moving image generated by selecting themoving-image preview button 116 is also similar.

FIG. 12 is a diagram showing an example of the imaging rules. In thisembodiment, the landmark type, the distance from the target, the imagingazimuth, the imaging altitude, and the field angle position are set asthe imaging rules.

The landmark type indicates the classification of the landmark. Forexample, high-rise buildings, mountains, bridges, houses, and the likeare set. Of course, other landmark classifications may be set. Note thatin this embodiment the landmark type corresponds to classificationinformation for classifying an object.

The distance from the target indicates the distance between the selectedlandmark and the drone 50. For example, if “distance 0” is set, adistance (position) from which imaging can be performed directly aboveor directly below a building serving as an object is a candidate point.Further, if “40%” is set, a distance from which imaging can be performedsuch that the object occupies 40% of the total height of the field angleof the camera of the drone 50 is a candidate point.

Further, for example, if the distance from the target is set to “140%”,the landmark is enlarged by 1.4 times and displayed from the state inwhich the landmark occupies 100% of the total height of the field angleof the camera. In other words, the drone 50 performs imaging at aposition closer to the landmark than when the distance from the targetis “100%”.

In other words, the distance from the target is defined as the distanceat which an image is captured, in which the landmark occupies a certainamount with respect to the total height of the field angle of thecamera.

The imaging azimuth indicates the direction in which the drone 50 imagesa target landmark. In this embodiment, north, south, east, west, anddirectly above are set for the landmark. The imaging altitude indicatesthe position with respect to the height of the object. For example, if“50%” is set, the position of 50% of the height of the building is acandidate point. Note that in this embodiment the distance from theobject and the imaging altitude correspond to the imaging positionrelative to the object.

The field angle position indicates the position where the object appearsin the image captured by the drone 50. For example, a position or adirection of the camera, from which the building can be displayed at thecenter, is a candidate point.

A plurality of candidate points is generated by a combination of thosevarious imaging rules. For example, a candidate point in the case wherethe building is imaged from directly above at the center of the image isgenerated according to the imaging rules set as follows: the landmarktype is “building”, the distance from the target is “distance 0(directly above)”, the imaging azimuth is “directly above”, the imagingaltitude is “120%”, and the field angle position is “center”. In otherwords, the imaging rules can be said to be imaging conditions of acandidate point. Note that in this embodiment the imaging azimuth andthe field angle position correspond to the display state of the objectin the predicted image.

The conditions of the imaging rules are not limited. For example, anyimaging rule may be set by the user. Note that in this embodiment thedistance from the object, the imaging azimuth, the imaging altitude, andthe field angle position correspond to the relative position between theobject and the mobile body. Note that in this embodiment the imagingrules correspond to rules for generating a predicted image relating toan instruction to select an object.

As a result, when the scenario plan information is generated, thescenario plan information such as the latitude and longitude, thealtitude, and the direction of the camera of the drone 50 can be set byselecting the candidate point, so that the scenario plan information canbe easily generated.

Third Embodiment

A drone imaging system 300 according to a third embodiment of thepresent technology will be described.

In the second embodiment, the candidate images of the plurality ofcandidate points corresponding to the selected landmark for each imagingrule are displayed in the candidate image display part 164. In the thirdembodiment, only one of the plurality of candidate points is randomlyselected, and a candidate image of the selected candidate point isgenerated. A candidate image is selected by image recognition as towhether a landmark is present in the generated candidate image.

FIG. 13 is a block diagram showing a functional configuration example ofa server apparatus 180 according to the third embodiment of the presenttechnology. The server apparatus 180 includes a GUI generation unit 181and a scenario plan information generation unit 182. The GUI generationunit 181 includes a recognizer acquisition unit 183, a candidate imagedetermination unit 184, and a candidate image holding unit 185 inaddition to the server apparatus 150 of the second embodiment. Note thatthe scenario plan information generation unit 182 is similar to that ofthe first embodiment, and thus the illustration thereof is omitted.

Similar to the second embodiment, the instruction informationacquisition unit 152 acquires instruction information relating to theselection of the transit point 171, and outputs the instructioninformation to the candidate point generation unit 153.

The candidate point generation unit 153 generates a candidate point onthe basis of an instruction from the user and imaging rules held in theimaging rule DB 155. In the third embodiment, only one candidate pointis selected, and a candidate image of the selected candidate point isgenerated.

The recognizer acquisition unit 183 acquires a recognizer for performingimage recognition on the predicted image generated by the candidateimage generation unit 154. For example, a recognizer corresponding tovarious uses such as a determination in which the candidate image is ascene or a building or an inspection of a deterioration state of thebuilding is acquired. Further, the instruction information acquisitionunit 152 may acquire instruction information relating to the acquisitionof the recognizer, and output the instruction information to therecognizer acquisition unit 183.

The candidate image determination unit 184 determines whether or not theselected landmark is present in the generated candidate image. In thisembodiment, the candidate image determination unit 184 determineswhether or not the reliability of the landmark in the candidate imageexceeds a predetermined threshold value. In other words, the recognizeris used to evaluate (score) whether or not the candidate image is animage according to the purpose.

Note that a specific algorithm or the like for performing imagerecognition is not limited, and, for example, machine learning may beused. For example, a template image indicating a landmark and a landmarkappearing in a candidate image may be determined by template matching.Further, for example, the accuracy of the candidate image may beimproved by matching using feature points or the like in an image of ahigh-accuracy landmark captured by a professional photographer.

The candidate image holding unit 185 holds a candidate image whosereliability is determined to exceed a predetermined threshold value bythe candidate image determination unit 184. In this embodiment, thecandidate image holding unit 185 keeps holding the candidate imagesuntil the number of candidate images whose reliability exceeds apredetermined threshold value reaches a predetermined number. When thenumber of candidate images reaches a predetermined number, the suppliedcandidate images are displayed in the candidate image display part 164.

In other words, the predicted image is generated by generating aprediction candidate image on the basis of the position information ofthe object serving as the selection target, and evaluating theprediction candidate image relating to the display state of the objectin the predicted image.

FIG. 14 is a flowchart showing a determination example for generating acandidate image. The processing of Step 401, Step 402, Step 406, Step407, Step 408, and Step 409 are the same as in the first embodiment, andthus description thereof is omitted.

With reference to FIG. 10, a landmark displayed in the map display part111 is selected by the user. One of a plurality of candidate points israndomly selected on the basis of the imaging rules linked to thelandmark by the candidate point generation unit 153, and a candidateimage of the candidate point is generated (Step 403).

For example, if the type of the landmark selected by the user ismountain, a candidate image is generated, which is captured from 10% ofthe height of the mountain from the west and is displayed such that themountain occupies 60% of the height of the field angle at the center ofthe field angle.

The candidate image determination unit 184 determines whether or not theselected landmark is present in the generated candidate image (Step404). For example, if the Tokyo tower is selected as a landmark by theuser, the candidate image determination unit 184 performs imagerecognition on the generated candidate image to determine whether theTokyo tower is present in the candidate image.

If it is determined that the selected landmark is present in thecandidate image (Yes in Step 404), the candidate image holding unit 185holds that candidate image. If the number of candidate images reaches apredetermined number (Yes in Step 405), the candidate image held by thecandidate image holding unit 185 is displayed in the candidate imagedisplay part 164 (Step 406).

If it is determined that the selected landmark is not present in thecandidate image (No in Step 404) or if the number of candidate imagesdoes not reach a prescribed number (No in Step 405), a candidate pointof the landmark selected by the candidate point generation unit 153 isgenerated, and a candidate image of the candidate point generated by thecandidate image generation unit 154 is newly generated.

Thus, it is possible to make the predicted image, which is displayedusing the evaluation result by the image recognizer, highly accurate.

Other Embodiments

The present technology is not limited to the embodiments described aboveand can provide various other embodiments.

FIG. 15 is a block diagram showing a hardware configuration example ofthe server apparatus 10. Of course, the hardware configuration exampleof the server apparatus 10 can be similarly implemented for the serverapparatuses 80, 150, and 180.

The server apparatus 10 includes a CPU 201, a read only memory (ROM)202, a RAM 203, an input/output interface 205, and a bus 204 thatconnects them to each other. A display unit 206, an input unit 207, astorage unit 208, a communication unit 209, a drive unit 210, and thelike are connected to the input/output interface 205.

The display unit 206 is a display device using liquid crystal,electro-luminescence (EL), or the like. The input unit 207 is, forexample, a keyboard, a pointing device, a touch panel, or otheroperation devices. In a case where the input unit 207 includes a touchpanel, the touch panel may be integrated with the display unit 206.

The storage unit 208 is a nonvolatile storage device and is, forexample, an HDD, a flash memory, or other solid-state memory. The driveunit 210 is, for example, a device capable of driving a removablerecording medium 211 such as an optical recording medium or a magneticrecording tape.

The communication unit 209 is a modem, a router, or other communicationdevice that can be connected to a LAN, a WAN, or the like forcommunicating with other devices. The communication unit 209 maycommunicate using either wired or wireless communication. Thecommunication unit 209 is often used separately from the serverapparatus 10.

In this embodiment, the communication unit 209 allows communication withother devices via the network.

The information processing by the server apparatus 10 having theabove-mentioned hardware configuration is implemented in cooperationwith the software stored in the storage unit 208, the ROM 202, or thelike and the hardware resources of the server apparatus 10.Specifically, the information processing method according to the presenttechnology is implemented when a program stored in the ROM 202 or thelike and configuring the software is loaded into the RAM 203 and thenexecuted.

The program is installed in the server apparatus 10, for example,through the recording medium 211. Alternatively, the program may beinstalled in the server apparatus 10 via a global network or the like.Moreover, any non-transitory computer-readable storage medium may beused.

In the third embodiment described above, the scanning plan informationof the scanning drone 60 is generated, and thus the scanning drone 60autonomously flies and the image data is acquired. The presenttechnology is not limited to the above, and image data may be acquiredby the user operating the scanning drone 60.

In the first embodiment and the second embodiment described above, theimaging conditions are displayed in the timeline in the timeline displaypart 113. The present technology is not limited to the above, and theimaging conditions such as the altitude, the airframe posture, and thecamera direction displayed in the timeline display part 113 may becontrolled by the selection of the user. For example, the user mayselect a timeline indicating the altitude of the drone 50 at the transitpoint and drag the timeline, so that the altitude may be controlled.

In the first embodiment and the second embodiment described above, the“distance from the target” of the imaging rules linked to the landmarkis defined as a distance at which an image is captured, in which thelandmark occupies a certain amount with respect to the total height ofthe field angle of the camera. The present technology is not limited tothe above, and it may be defined as a distance at which an image iscaptured, in which the landmark occupies a certain amount with respectto the horizontal length perpendicular to the height direction of thefield angle of the camera. In addition, the distance from the targetalso includes a case where the candidate image is a photograph or thelike captured as looking upward and the lower end and the upper endthereof are not captured.

In the first embodiment, the second embodiment, and the third embodimentdescribed above, the server apparatus provides the drone imaging systemto the user terminal 30 via the network 35. The present technology isnot limited to the above, and the configuration that functions as theserver apparatus may be included in the user terminal 30 or the drone50.

In the first embodiment, the second embodiment, and the third embodimentdescribed above, the drone 50 and the scanning drone 60 execute thescenario plan information and the scanning plan information by oneautonomous flight. The present technology is not limited to the above.For example, if it is determined that a battery or the like does notlast until the scenario plan information and the scanning planinformation are ended, information of to which point the image has beencaptured may be held. Alternatively, the autonomous flight may becontinued from a position in the middle of imaging after the battery isreplaced or charged by RTH (Return To Home) or the like. Further, thedrone 50 and the scanning drone 60 may have a moving mechanism that ismovable over the ground or water as well as in aerial flight.

In the first embodiment, the second embodiment, and the third embodimentdescribed above, the plan generating GUI is presented as an application.The present technology is not limited to toe above. For example, a website relating to the drone development system may be constructed, and apredetermined web page within the web site may be accessed through theuser terminal 30, so that the plan generating GUI may be presented.

The information processing apparatus, the information processing method,the program, and the information processing system according to thepresent technology may be performed, and the information processingapparatus according to the present technology may be constructed, bylinking a computer mounted on a communication terminal with anothercomputer capable of communicating via a network or the like.

In other words, the information processing apparatus, the informationprocessing method, the program, and the information processing systemaccording to the present technology can be performed not only in acomputer system formed of a single computer, but also in a computersystem in which a plurality of computers operates cooperatively. Notethat, in the present disclosure, the system refers to a set ofcomponents (such as apparatuses and modules (parts)) and it does notmatter whether all of the components are in a single housing. Thus, aplurality of apparatuses accommodated in separate housings and connectedto each other through a network, and a single apparatus in which aplurality of modules is accommodated in a single housing are both thesystem.

The execution of the information processing apparatus, the informationprocessing method, the program, and the information processing systemaccording to the present technology by the computer system includes, forexample, both a case in which the generation of the scenario planinformation, the acquisition of image data, the generation of thepredicted image, and the like are performed by a single computer; and acase in which the respective processes are performed by differentcomputers. Further, the execution of each process by a predeterminedcomputer includes causing another computer to perform a portion of orall of the process and obtaining a result thereof.

In other words, the information processing apparatus, the informationprocessing method, the program, and the information processing systemaccording to the present technology are also applicable to aconfiguration of cloud computing in which a single function is sharedand cooperatively processed by a plurality of apparatuses through anetwork.

The respective configurations of the GUI generation unit, the image dataacquisition unit, the predicted-image generation unit, the plangeneration unit, and the like; the control flow of the communicationsystem; and the like described with reference to the respective figuresare merely embodiments, and any modifications may be made theretowithout departing from the spirit of the present technology. In otherwords, for example, any other configurations or algorithms for purposeof practicing the present technology may be adopted.

Note that the effects described in the present disclosure are merelyillustrative and not restrictive, and other effects may be obtained. Theabove description of the plurality of effects does not necessarily meanthat these effects are simultaneously exhibited. It means that at leastone of the above-mentioned effects can be obtained depending on theconditions and the like, and of course, there is a possibility that aneffect not described in the present disclosure can be exhibited.

At least two of the features among the features of the embodimentsdescribed above can also be combined. In other words, various featuresdescribed in the respective embodiments may be combined discretionarilyregardless of the embodiments.

Note that the present technology may also take the followingconfigurations.

(1) An information processing apparatus, including:

an acquisition unit that acquires image data relating to a predeterminedregion on a map;

an image generation unit that generates a predicted image on the basisof the image data, the predicted image being predicted to be acquiredwhen imaging is performed within the predetermined region; and

a presentation unit that presents the predicted image on the basis of aninstruction relating to generation of plan information relating tomovement and imaging of a mobile body having an imaging function withinthe predetermined region.

(2) The information processing apparatus according to (1), in which

the presentation unit outputs a graphical user interface (GUI) includingthe predicted image for inputting the instruction relating to thegeneration of the plan information.

(3) The information processing apparatus according to (1) or (2), inwhich

the image generation unit generates the predicted image on the basis ofan instruction relating to at least one of a position within thepredetermined region or an imaging condition.

(4) The information processing apparatus according to (3), in which

the imaging condition includes at least one of an imaging direction, animaging time, or environment information relating to the predeterminedregion.

(5) The information processing apparatus according to any one of (1) to(4), in which

the image generation unit generates, on the basis of an instruction toselect an object present within the predetermined region, the predictedimage in which the object is imaged.

(6) The information processing apparatus according to (5), in which

the image generation unit generates the predicted image on the basis ofa generation rule of the predicted image relating to the instruction toselect the object.

(7) The information processing apparatus according to (6), in which

the generation rule includes classification information for classifyingthe object and at least one of information of a relative imagingposition relative to the object or information of a display state of theobject within the predicted image, as information associated with theclassification information.

(8) The information processing apparatus according to any one of (5) to(7), in which

the image generation unit generates the predicted image by generating aprediction candidate image on the basis of position information of theobject serving as a selection target and evaluating the predictioncandidate image regarding a display state of the object within thepredicted image.

(9) The information processing apparatus according to any one of (1) to(8), further including

a plan generation unit that generates the plan information on the basisof an input instruction relating to the generation of the planinformation.

(10) The information processing apparatus according to (9), in which

the plan generation unit generates the plan information on the basis ofan instruction to select the presented predicted image.

(11) The information processing apparatus according to any one of (1) to(10), in which

the plan information includes at least one of a transit point, a movingtime, or an imaging condition.

(12) The information processing apparatus according to any one of (1) to(11), in which

the image data is image data acquired when a scanning mobile body havingan imaging function performs imaging while scanning the predeterminedregion.

(13) The information processing apparatus according to any one of (1) to(12), in which

the image data includes omnidirectional image data.

(14) The information processing apparatus according to any one of (1) to(13), further including

a control unit that controls an operation relating to the movement andthe imaging of the mobile body having the imaging function on the basisof the plan information.

(15) The information processing apparatus according to (12), furtherincluding

a scanning generation unit that generates scanning plan informationrelating to scanning and imaging of the scanning mobile body within thepredetermined region.

(16) The information processing apparatus according to (15), in which

the scanning plan information includes cost information relating to ascanning route, and

the cost information is generated on the basis of a scanning route thathas been taken in a past.

(17) An information processing method, which is executed by a computersystem, the method including:

acquiring image data relating to a predetermined region on a map;

generating a predicted image on the basis of the image data, thepredicted image being predicted to be acquired when imaging is performedwithin the predetermined region; and

presenting the predicted image on the basis of an instruction relatingto generation of plan information relating to movement and imaging of amobile body having an imaging function within the predetermined region.

(18) A program causing a computer system to execute the steps of:

acquiring image data relating to a predetermined region on a map;

generating a predicted image on the basis of the image data, thepredicted image being predicted to be acquired when imaging is performedwithin the predetermined region; and

presenting the predicted image on the basis of an instruction relatingto generation of plan information relating to movement and imaging of amobile body having an imaging function within the predetermined region.

(19) An information processing system, including:

an information processing apparatus including

-   -   an acquisition unit that acquires image data relating to a        predetermined region on a map,    -   an image generation unit that generates a predicted image on the        basis of the image data, the predicted image being predicted to        be acquired when imaging is performed within the predetermined        region,    -   a presentation unit that presents the predicted image on the        basis of an instruction relating to generation of plan        information relating to movement and imaging of a mobile body        having an imaging function within the predetermined region, and    -   a plan generation unit that generates the plan information on        the basis of an input instruction relating to the generation of        the plan information; and

a mobile body that includes an imaging unit and performs imaging whilemoving within the predetermined region on the basis of the planinformation generated by the information processing apparatus.

REFERENCE SIGNS LIST

-   10 server apparatus-   11, 70, 90 communication control unit-   12, 81, 151, 181 GUI generation unit-   13 scenario plan information generation unit-   18 image data acquisition unit-   19 predicted-image generation unit-   20 image processing unit-   50 drone-   51 imaging device-   60 scanning drone-   63 camera-   68 action planning unit-   69 cost map generation unit-   82 scanning plan information unit-   86 scanning plan setting unit-   100 drone imaging system-   110, 160 plan generating GUI-   154 candidate image generation unit-   155 imaging rule DB-   184 candidate image determination unit

1. An information processing apparatus, comprising: an acquisition unitthat acquires image data relating to a predetermined region on a map; animage generation unit that generates a predicted image on a basis of theimage data, the predicted image being predicted to be acquired whenimaging is performed within the predetermined region; and a presentationunit that presents the predicted image on a basis of an instructionrelating to generation of plan information relating to movement andimaging of a mobile body having an imaging function within thepredetermined region.
 2. The information processing apparatus accordingto claim 1, wherein the presentation unit outputs a graphical userinterface (GUI) including the predicted image for inputting theinstruction relating to the generation of the plan information.
 3. Theinformation processing apparatus according to claim 1, wherein the imagegeneration unit generates the predicted image on the basis of aninstruction relating to at least one of a position within thepredetermined region or an imaging condition.
 4. The informationprocessing apparatus according to claim 3, wherein the imaging conditionincludes at least one of an imaging direction, an imaging time, orenvironment information relating to the predetermined region.
 5. Theinformation processing apparatus according to claim 1, wherein the imagegeneration unit generates, on a basis of an instruction to select anobject present within the predetermined region, the predicted image inwhich the object is imaged.
 6. The information processing apparatusaccording to claim 5, wherein the image generation unit generates thepredicted image on a basis of a generation rule of the predicted imagerelating to the instruction to select the object.
 7. The informationprocessing apparatus according to claim 6, wherein the generation ruleincludes classification information for classifying the object and atleast one of information of a relative imaging position relative to theobject or information of a display state of the object within thepredicted image, as information associated with the classificationinformation.
 8. The information processing apparatus according to claim5, wherein the image generation unit generates the predicted image bygenerating a prediction candidate image on a basis of positioninformation of the object serving as a selection target and evaluatingthe prediction candidate image regarding a display state of the objectwithin the predicted image.
 9. The information processing apparatusaccording to claim 1, further comprising a plan generation unit thatgenerates the plan information on a basis of an input instructionrelating to the generation of the plan information.
 10. The informationprocessing apparatus according to claim 9, wherein the plan generationunit generates the plan information on a basis of an instruction toselect the presented predicted image.
 11. The information processingapparatus according to claim 1, wherein the plan information includes atleast one of a transit point, a moving time, or an imaging condition.12. The information processing apparatus according to claim 1, whereinthe image data is image data acquired when a scanning mobile body havingan imaging function performs imaging while scanning the predeterminedregion.
 13. The information processing apparatus according to claim 1,wherein the image data includes omnidirectional image data.
 14. Theinformation processing apparatus according to claim 1, furthercomprising a control unit that controls an operation relating to themovement and the imaging of the mobile body having the imaging functionon a basis of the plan information.
 15. The information processingapparatus according to claim 12, further comprising a scanninggeneration unit that generates scanning plan information relating toscanning and imaging of the scanning mobile body within thepredetermined region.
 16. The information processing apparatus accordingto claim 15, wherein the scanning plan information includes costinformation relating to a scanning route, and the cost information isgenerated on a basis of a scanning route that has been taken in a past.17. An information processing method, which is executed by a computersystem, the method comprising: acquiring image data relating to apredetermined region on a map; generating a predicted image on a basisof the image data, the predicted image being predicted to be acquiredwhen imaging is performed within the predetermined region; andpresenting the predicted image on a basis of an instruction relating togeneration of plan information relating to movement and imaging of amobile body having an imaging function within the predetermined region.18. A program causing a computer system to execute the steps of:acquiring image data relating to a predetermined region on a map;generating a predicted image on a basis of the image data, the predictedimage being predicted to be acquired when imaging is performed withinthe predetermined region; and presenting the predicted image on a basisof an instruction relating to generation of plan information relating tomovement and imaging of a mobile body having an imaging function withinthe predetermined region.
 19. An information processing system,comprising: an information processing apparatus including an acquisitionunit that acquires image data relating to a predetermined region on amap, an image generation unit that generates a predicted image on abasis of the image data, the predicted image being predicted to beacquired when imaging is performed within the predetermined region, apresentation unit that presents the predicted image on a basis of aninstruction relating to generation of plan information relating tomovement and imaging of a mobile body having an imaging function withinthe predetermined region, and a plan generation unit that generates theplan information on a basis of an input instruction relating to thegeneration of the plan information; and a mobile body that includes animaging unit and performs imaging while moving within the predeterminedregion on a basis of the plan information generated by the informationprocessing apparatus.